Automation & AI · Checklist
An AI-readiness checklist for SMEs
AI readiness is operational readiness.
Last reviewed: July 13, 2026
3 min · Read
Executive summary
Before adding a model, define the task, data boundary, acceptable error, human approval, fallback and record of what happened. A controlled workflow is more valuable than a broad autonomous promise.
Choose a support task
Good initial tasks include summarizing a known document set, classifying requests, drafting from approved context, extracting fields or preparing QA.
Avoid open-ended authority over prices, contracts, payments, refunds, sensitive sending or public claims.
Set the boundary
List allowed sources, prohibited data, retention expectations, roles and the decision the output may influence.
Define whether the output is a suggestion, draft, score or routing signal. Make that status visible.
Evaluate and operate
Create representative examples, expected outputs and failure cases. Review false positives and omissions, and keep a fallback that does not depend on the model.
Assign an owner for prompt, source and policy changes.
Practical checklist
- Is the task narrow?
- Is the source approved?
- Is sensitive data minimized?
- Is output status visible?
- Is human approval explicit?
- Are failures testable?
- Is there a fallback?
- Who owns changes?
Related solutions
- AI & Operational Intelligence
- Operations & Workflow Automation
This article contains no external quantitative claim and no disclosed affiliate relationship.
Next step
See how this decision applies to your business.
The diagnosis connects the framework to your real process, data and constraints.